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Find the optimal product portfolio with TURF

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TURF analysis helps you improve the performance of your product portfolio

TURF (Total Unduplicated Reach and Frequency) helps you to identify the optimal number of products in your portfolio. You will understand which products you should add to maximise reach.

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Uncover consumers’ real preferences

TURF is a method used to gain insights about market potential and optimal portfolio strategy because it shows the incremental potential of adding a product to the existing portfolio.

When to use TURF analysis

TURF is used for various topics, including flavours, pack sizes, colour options or content options.

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Benefits and value provided

TURF analysis answers business questions such as:

  • How many products should be in our portfolio
  • Which products should we have in the portfolio
  • Should we launch these new products on the market?
  • Should we remove any products from our portfolio?
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More Methods

Discover other options

Conjoint Analysis

Understand what your customers value in your product with Conjoint. Learn how much each feature influences your demand and sales, and estimate what price premium you can charge for improved features.

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NLP (Natural Language Processing)

Including open-ended questions in a survey can generate thousands of sentences to make sense of. But this isn’t a problem with Cambri’s proprietary NLP solution. In a matter of seconds, you’ll get an understanding of what consumers are talking about, and whether the sentiment is positive, negative or neutral.

Read more
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Cluster Analysis

Segmentation helps identify homogeneous segments with unique preferences, as well as understand the interrelationship between needs or drivers. It allows you to uncover the preference of different attributes for a particular segment that may be different from the market as a whole.

Read more
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MaxDiff

MaxDiff helps identify consumer segments and why certain consumers are attracted to certain products. It uses an indirect questioning technique to ask respondents to choose their favourite from a subset of attributes and uses statistical modelling to estimate the utility respondents assign to each attribute.

Read more
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